📣MuJoCo announcement 📣 Thrilled to share that Google DeepMind has unveiled MuJoCo-Warp at NVIDIA's #GTC25! 🚀 We've expanded our open-source MuJoCo simulator with MuJoCo-Warp, leveraging NVIDIA’s Warp framework for incredible acceleration. This marks a significant step in

1/ While most RL methods use shallow MLPs (~2–5 layers), we show that scaling up to 1000-layers for contrastive RL (CRL) can significantly boost performance, ranging from doubling performance to 50x on a diverse suite of robotic tasks. Webpage+Paper+Code: wang-kevin3290.github.io/scaling-crl/

🚀 We’re releasing #LocoMuJoCo2 — An extensive library for whole-body imitation & RL. 🔥 Highlights: - Supports MuJoCo & MJX - Clean JAX impl of PPO, GAIL, AMP, DeepMimic - 22K+ trajectories per humanoid - Add your humanoid easily 🔗 github.com/robfiras/loco-… 🧵Details 👇

IAS is at RLDM 2025! We have many exiting works to share, so come to our posters and talk to Tim Schneider, Nico Bohlinger, Théo Vincent @RLC & Kay Pompetzki!

Do you want to deploy a navigation stack on a cheap quadruped robot? Take a look at our latest ECMR paper, "Robust Localization, Mapping, and Navigation for Quadruped Robots". In our work, we tackle the issues arising from the combination of low-cost robots and RL policies